Proactive university library book recommender system

Show simple item record Mekonnen, Tadesse Zewdu 2022-12-12T02:50:24Z 2022-12-12T02:50:24Z 2021
dc.description M. Tech. (Department of Information Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. en_US
dc.description.abstract Too many options on the internet are the reason for the information overload problem to obtain relevant information. A recommender system is a technique that filters information from large sets of data and recommends the most relevant ones based on people‟s preferences. Collaborative and content-based techniques are the core techniques used to implement a recommender system. A combined use of both collaborative and content-based techniques called hybrid techniques provide relatively good recommendations by avoiding common problems arising from each technique. In this research, a proactive University Library Book Recommender System has been proposed in which hybrid filtering is used for enhanced and more accurate recommendations. The prototype designed was able to recommend the highest ten books for each user. We evaluated the accuracy of the results using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). A measure value of 0.84904 MAE and 0.9579 RMSE found by our system shows that the combined use of both techniques gives an improved prediction accuracy for the University Library Book Recommender System. en_US
dc.language.iso en en_US
dc.publisher Vaal University of Technology en_US
dc.subject University Library Book Recommender System en_US
dc.subject Collaborative and content-based techniques en_US
dc.subject Hybrid techniques en_US
dc.subject Hybrid filtering en_US
dc.subject Mean Absolute Error (MAE) en_US
dc.subject Root Mean Squared Error (RMSE) en_US
dc.subject.lcsh Dissertations, Academic -- South Africa en_US
dc.subject.lcsh Artificial intelligence -- Data processing en_US
dc.subject.lcsh Electronic data processing en_US
dc.subject.lcsh Self-organizing systems en_US
dc.subject.lcsh Recommender systems (Information filtering) en_US
dc.title Proactive university library book recommender system en_US
dc.type Thesis en_US
dc.contributor.supervisor Zuva, Tranos, Prof.

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DigiResearch

Advanced Search

My Account